code: def deepen(self, loc, new_layer_config, input_dim):
      if loc["multi-branch"] == "in_bottle":
          assert self.in_bottle is not None, "Invalid"
          return self.in_bottle.deepen(
              loc["layer"], new_layer_config, input_dim
          )
      elif loc["multi-branch"] == "out_bottle":
          assert self.out_bottle is not None, "Invalid"
          if self.merge == "concat":
              input_dim = np.sum(
                  [branch.out_features_dim for branch in self.branches]
              )
          else:
              input_dim = self.branches[0].out_features_dim
          return self.out_bottle.deepen(
              loc["layer"], new_layer_config, input_dim
          )
      elif loc["multi-branch"] == "branch":
          if self.in_bottle is not None:
              input_dim = self.in_bottle.out_features_dim
          return self.branches[loc["branch"]].deepen(
              loc["layer"], new_layer_config, input_dim
          )
      else:
          raise ValueError("Do not support %s" % loc["multi-branch"])
  
file_path: auptimizer/src/aup/Proposer/eas/models/layer_multi_branch.py
imports: import tensorflow
  import numpy
  from .layer_cascade import LayerCascade
label_desc: Use image node_id 13 for calling the LayerMultiBranch obj's underlying member method code with example usage: obj.deepen(loc, new_layer_config, input_dim) and returns: self, self, self